KR102304745B1 - System for recommanding charging point of an electric vehicle - Google Patents

Abstract

The present invention relates to an electric vehicle charging station recommendation system, comprising: an EV departure time recognition module for recognizing a departure time of an electric vehicle; a user EV P.O.I recognition module for recognizing a place frequently visited by the user of the electric vehicle; a user EVE trajectory recognition module for recognizing a preferred route among the routes that the user frequently travels from a departure point to a destination; a user CPI PIO recognition module for recognizing the user's favorite charging station; a CPI population recognition module for recognizing the charging state of a charging station adjacent to the preferred road in real time; a charging start/end charging amount recognition module for recognizing a charging amount at the start and end of charging of the electric vehicle; and a control unit communicatively connected to an electric vehicle or a mobile device owned by a user of the electric vehicle, and recommending a charging station capable of charging the electric vehicle to the user in order to charge an amount of charge required for the electric vehicle to reach the destination.

Description

Electric vehicle charging station recommendation system {SYSTEM FOR RECOMMANDING CHARGING POINT OF AN ELECTRIC VEHICLE}

The present invention relates to an electric vehicle charging station recommendation system and method for recommending an optimal charging station that can be charged to a customer.

Interest in the development of eco-friendly vehicles is growing as the most effective alternative to achieving national carbon dioxide reduction targets due to the strengthening of international regulations on greenhouse gas emissions. There is an urgent need to build an electric vehicle charging infrastructure in line with the completed electric vehicle mass production schedule.

Unlike general internal combustion engine vehicles, electric vehicles are composed of batteries, electric motors, inverters, converters and BMS (Battery Management System), and rechargeable batteries are used for batteries.

A prerequisite for the dissemination of electric vehicles is to construct a charging infrastructure, and countries around the world are developing models for charging infrastructure and services and are conducting demonstration projects.

On the other hand, electric vehicle (EV) charging station operators are disclosing the operating status of chargers (charging stations, CP: Charging Point) to attract customers.

Conventionally, a customer directly finds and charges a charging station that can be charged during his or her schedule with reference to information disclosed by a charging station operator.

That is, when a customer (electric vehicle user) searches for the charger operation status disclosed by the charging station operator and requests the charging station usage status information from the control system, the control system provides the necessary information to the customer again.

However, the existing charger usage status information service is a system in which a user can obtain necessary information only after a customer's search and request. For this reason, there is a inconvenience in that the customer has to request information on the charging status of the charger from the control system every time the electric vehicle is charged.

The present invention was created to solve the problems of the prior art, and if the customer is initially registered as a member, an electric vehicle that can recommend an optimal charging station to the customer at an appropriate time without the customer making a separate request to the control system An object of the present invention is to provide a charging station recommendation system and method.

In order to achieve the above object, an electric vehicle charging station recommendation system according to the present invention includes an EVE departure time recognition module for recognizing a start time of an electric vehicle; a user EV P.O.I recognition module for recognizing a place frequently visited by the user of the electric vehicle; a user EVE trajectory recognition module for recognizing a preferred route among the routes that the user frequently travels from a departure point to a destination; a user CPI PIO recognition module for recognizing the user's favorite charging station; a CPI population recognition module for recognizing the charging state of a charging station adjacent to the preferred road in real time; a charging start/end charging amount recognition module for recognizing a charging amount at the start and end of charging of the electric vehicle; and a control unit communicatively connected to an electric vehicle or a mobile device owned by a user of the electric vehicle, and recommending a charging station capable of charging the electric vehicle to the user in order to charge an amount of charge required for the electric vehicle to reach the destination.

According to an example related to the present invention, the controller may recommend another charging station with a shorter charging time even when bypassing the charging station in consideration of a charging standby time when arriving at a charging station adjacent to the preferred road.

According to an example related to the present invention, a charging station adjacent to the road moving from the departure point to the destination has a plurality of chargers, and the control unit determines that the user arrives at the charging station compared to the charging completion time of each of the plurality of chargers. By calculating the time, when arriving at the charging station, it is possible to recommend chargers capable of charging in the order of the charging start time.

According to an example related to the present invention, the user EVE P.O.I recognition module may recognize a place frequently visited by time zone.

According to an example related to the present invention, the user CPPOI recognition module may search for a charger that can be used as a membership card of the favorite charging station.

According to an example related to the present invention, the vehicle may further include a traffic situation recognition module in EVE trajectory that recognizes the traffic situation on the preferred road when the electric vehicle starts and recommends a charging station in a section where there is no congestion. have.

According to an example related to the present invention, further comprising a weather recognition module for recognizing whether it is snowing or raining, the control unit recommends charging just before snow or rain when the recommended charging station is outdoors An indoor charging station can be recommended.

According to an example related to the present invention, as the CPI population recognition module uploads information at the time of member authentication or charging start to the charging station to the server of the control system, the user or customer uploads information to the charging station adjacent to the user's preferred route. The charging status of the battery can be recognized in real time.

According to an example related to the present invention, the user EVE P.O.I recognition module can search for charging stations that can be charged upon arrival of a registered customer based on a charging service membership card near the charging station preferred by the user and the preferred charging station. have.

According to an example related to the present invention, the user EVE trajectory recognition module may search for a charging station existing on a preferred route when moving from the origin to the destination.

According to an example related to the present invention, the user CPPOI recognition module may recommend a charging station that can be charged according to the user's charging pattern at the time of departure from the frequently visited place.

According to an example related to the present invention, a charging time/cycle recognition module for recognizing the user's charging time and charging period may be further included.

According to an example related to the present invention, the CPI population recognition module determines the charging status of a charging station based on the time when the user is charging, and based on the location of the charging station, according to the number of chargers held by each charging station The density of each charging station can be estimated.

The effect of the electric vehicle charging station recommendation system according to the present invention will be described as follows.

First, as long as the customer (user) is registered as a member at the electric vehicle control center, the electric vehicle charging station recommendation system notifies the user at an appropriate time without the customer making a separate search and request for the charging status, etc., thereby improving user convenience can do it

Second, the electric vehicle charging station recommendation system can track customer traces based on the information coming into the electric vehicle control center.

Third, the electric vehicle charging station recommendation system includes the location where the electric vehicle is parked (POI), the trajectory (preferred road) connecting these places (POI), the charging station visited by the customer within this trajectory, and the customer near the charging station. The best charging stations that can be charged by connecting all of this information, such as charging stations that can be charged at the time of arrival, adjusting the charging timing according to the weather if the recommended charging station is outdoors, and taking into account traffic conditions and the amount of charging required to get to the destination can be found and recommended to customers.

Fourth, the charging station operation status referenced by the user is based on the member's authentication/charging information coming from the EV control center, and the density of the charging station can be predicted based on the member's EV density within the GPS radius of the charging station.

Fifth, the charger operation status information provided to the user by the electric vehicle charging station recommendation system of the present invention can be obtained more quickly than the charger operation status that the user can check with a delay of 5 to 30 minutes through the Ministry of Environment.

1 is a conceptual diagram showing a module constituting an electric vehicle charging station recommendation system according to the present invention.
FIG. 2 is a block diagram for controlling the electric vehicle charging station recommendation system of FIG. 1 .
3 is a conceptual diagram illustrating an example of a semantic web as a method of implementing the electric vehicle charging station recommendation system in FIG. 1 .
4 is a conceptual diagram illustrating a semantic web for implementing the electric vehicle charging station recommendation system according to the present invention.
5 is a conceptual diagram for explaining a method of recognizing a user's charging pattern situation by the electric vehicle charging station recommendation system according to the present invention.
6 is a conceptual diagram for explaining a method for inferring a semantic situation for the electric vehicle charging station recommendation system of the present invention to recommend a charging place/time point to a user based on a probability-based state diagram.
7 is a conceptual diagram illustrating a state in which a notification message for charging time and charger recommendation is delivered to a dashboard of a user using a car navigation system.
8 is a conceptual diagram illustrating a state in which a notification message for recommending a charging time and a charging station that can be charged is delivered to a user's phone using a car navigation system.
9 is a conceptual diagram for specifically explaining the configuration of a user EVE POI recognition module and a user EVE trajectory recognition module of the present invention.
10 is a conceptual diagram illustrating a user CP PIO recognition module of the present invention.
11 is a conceptual diagram for explaining the configuration of a charging start/end SoC and a charging time/period recognition module of the present invention.
12 is a conceptual diagram for explaining an example of a method for recommending an electric vehicle charging station according to the present invention.
13 is a conceptual diagram illustrating a method for recommending an electric vehicle charging station according to an embodiment of the present invention.

Hereinafter, the embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but the same or similar components are assigned the same reference numerals regardless of reference numerals, and overlapping descriptions thereof will be omitted. The suffixes "module" and "part" for the components used in the following description are given or mixed in consideration of only the ease of writing the specification, and do not have a meaning or role distinct from each other by themselves. In addition, in describing the embodiments disclosed in the present specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in the present specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in the present specification, and the technical spirit disclosed herein is not limited by the accompanying drawings, and all changes included in the spirit and scope of the present invention , should be understood to include equivalents or substitutes.

Terms including an ordinal number, such as first, second, etc., may be used to describe various elements, but the elements are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

When a component is referred to as being “connected” or “connected” to another component, it is understood that the other component may be directly connected or connected to the other component, but other components may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that no other element is present in the middle.

The singular expression includes the plural expression unless the context clearly dictates otherwise.

In the present application, terms such as "comprises" or "have" are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

In the present invention, an electric vehicle is an eco-friendly vehicle, that is, an electric vehicle (EV) that drives a wheel using a power source of a battery, a hybrid electric vehicle (HEV), a plug-in hybrid vehicle (PHEV), a fuel cell (FCEV) Electric Vehicle) can be understood as a concept including. A core control device of a BMS (Battery Management System) may be installed inside the electric vehicle.

BMS manages drivable distance prediction, full charging, overcharging prevention, and equalizing charging between cells. It includes a battery replacement notification function through failure management of battery cells or modules and prediction of battery life.

The electric vehicle charging station recommendation system according to the present invention is a system that notifies the customer of the charger use state information, the electric vehicle charging place and the charging time at an appropriate time even if the customer does not request the charger use state information from the control system.

In the figure above, 1) information is the member information registered in the service company registered in the control system. If the above 1) information is registered only once for the first time, additional registration is not required. This is because the initially registered member information is not only registered with the service company, but also registered as customer management information in the program in the control system.

Here, the control system is an electric vehicle control system.

The service providers may include, for example, ChargEV, S-Traffic, Korea Charging (Happy Charger), the Ministry of Environment, and Korea Electric Power Corporation. The service provider is not limited thereto, and may change and update.

The control system may include information about charging an electric vehicle at an appropriate time, for example, information on the status of use of a charger. The control system may recommend charging locations and charging times according to charging and driving patterns at appropriate times to registered member customers.

To this end, the control system includes an electric vehicle charging station recommendation system that provides information on various electric vehicle charging for customer convenience.

The electric vehicle charging station recommendation system may be a Frame Work agency. The electric vehicle charging station recommendation system may be an AI (artificial intelligence) charging robot. The electric vehicle charging station recommendation system may be one of the programs installed in the control system. Electric vehicle charging station recommendation system AI (artificial intelligence) charging infrastructure can also be named.

The electric vehicle charging station recommendation system is configured to enable two-way communication with member customers (including mobile devices the customer is carrying). The electric vehicle charging station recommendation system may be configured to enable two-way communication with the electric vehicle used by the customer. The electric vehicle charging station recommendation system is configured to enable two-way communication with the control system. The electric vehicle charging station recommendation system is configured to enable two-way communication with the electric vehicle charging station 23 or the electric vehicle charger.

1 is a conceptual diagram showing a module constituting an electric vehicle charging station recommendation system according to the present invention. FIG. 2 is a block diagram for controlling the electric vehicle charging station recommendation system of FIG. 1 .

The electric vehicle charging station recommendation system of the present invention recognizes a User EV POI recognition module 10, a User EV Trajectory recognition module 11, and a User CP POI recognition module Module (12), charging start/end SoC and charging time/cycle recognition module (13), CP Population recognition module (14), EV start time recognition module (15), EV trajectory ( EV Trajectory) includes a traffic situation recognition module 16 and a weather recognition module 17 .

The electric vehicle charging station recommendation system (AI charging infrastructure) of the present invention is configured to analyze data by the above module and recommend an optimal charging station to the user at an appropriate time.

In the present specification, POI (Point of Interest) refers to a specific location in the real world or a map or drawing that a specific person is interested in in a general sense, but in the present invention, "a place where an electric vehicle 19 is parked" means

The user EVE PIO recognition module 10 is configured to analyze data using an Open API (Application Programming Interface). Open API is an open application development environment.

The user EVE POI recognition module 10 is configured to recognize a place (a parking lot; POI) that the user frequently visits by time using an Open API. For example, a place the user frequently goes to may be a home, a stay, or a company (a place where the user regularly works). A stay means a place where the user stays for more than a preset time.

The user EVE trajectory recognition module 11 is configured to recognize a preferred path 22 (TRAJECTORY) when moving from the first POI1 to the second POI2 using the Open API. For example, the trejectory is a route 22 that the user prefers among the roads (roads) from home (POI1) to work (POI2).

The user CPI PIO recognition module 12 is configured to recognize the favorite charging station 23 . CP (Charging Point) means a charging place or a charger. The user CP PIO module is configured to search for a charger that can be used with a membership card of a user's favorite charging station 23 in one CP Population in which a plurality of chargers (CP) are gathered. For example, the Happy Charger card may be used as the membership card of the favorite charging station 23 . The Happy Charger Card can be used to charge chargers (CPs) such as Korea Electric Power Corporation, Ministry of Environment, and GNTel.

The charging time/end SoC (State of Charge; meaning state of charge or amount of charge) recognition module 131 is configured to recognize the SoC at the start of charging and the SoC at the end of charging.

In addition, the charging time/period recognition module 132 is configured to recognize the charging time and the charging period. The charging time/period recognition module 132 may receive a signal from the BMS of the electric vehicle 19 and recognize it.

The CPI population recognition module 14 is configured to recognize the real-time charging state of the charging station 23 adjacent to the user's trejectory (preferred road 22). The CP population refers to the degree to which charging stations (CP) are dense, that is, the density of charging stations.

When the user authenticates the rotation to the charger (CP) and starts charging, the information is uploaded to the server of the control center 21 of the electric vehicle 19, and the CP population recognition module 14 analyzes the logging data of the EV control center 21 The real-time charging state of the charging station 23 may be recognized.

The CPI population recognition module 14 may recommend an optimal charger to the customer in consideration of the density of member electric vehicles 19 within a radius close to the GPS of the charging station 23 .

For example, it is possible to estimate the number of chargers in the charging station 23 adjacent to the user trejectory as n (one cluster), and predict the charger (idle CP) that can be charged without waiting when the user arrives at the location.

For example, in the figure above, assuming that charging stations 1 and 2 are adjacent to each other and charging stations 3 are far from charging stations 1 and 2, charging stations 1 and 2 can be grouped into one cluster. Charging station 1 has two chargers CP3 and CP4, and charging station 2 has one charger CP 1.

Charging Station 3 is a cluster separate from Charging Stations 1 and 2, and has two chargers CP2 and CP 5.

은 충전 중임을 표시하고, 속이 빈 빨간색 원형으로 표시된

은 충전 대기 중임을 표시한다.marked with a solid red circle

indicates charging, indicated by a hollow red circle

indicates that it is waiting for charging.

The EV start time recognition module is configured to recognize the start time of the electric vehicle 19 through the following two methods.

First, the EVE departure time recognition module 15 may recognize the user's mobile phone 20 . For example, the departure time of the electric vehicle 19 may be recognized through the time when the user connects to the Bluetooth of the electric vehicle 19 using the mobile phone 20 .

Second, the EVE departure time recognition module 15 may predict the departure time from the POI through LEARNING.

The traffic situation awareness module 16 in the EVE trajectory is configured to recognize the traffic situation in the user's preferred route 22 . For example, when traffic is congested on the preferred path 22 , it may be recommended to detour the preferred path 22 .

User CP PIO recognition module 12, charging start/end SoC and charging time/period recognition module 132, CP population recognition module 14, EVE departure time recognition module 15, and traffic conditions in EVE trajectory Each of the recognition modules 16 may analyze logging data of the electric vehicle 19 control system.

The weather recognition module 17 may analyze data using a web service. The weather recognition module 17 is configured to recognize snow or rain when the charger to be recommended is outdoors.

The electric vehicle charging station recommendation system may include a control unit 18 . The control unit 18 includes the above-described user EVE PIO recognition module 10, user EVE trajectory recognition module 11, user CPI PIO recognition module 12, charging start/end SoC, and charging time/cycle recognition module. 132 , it is connected to the CP population recognition module 14 , the EVE departure time recognition module 15 , the EVE trajectory traffic situation recognition module 16 , and the weather recognition module 17 . The control unit 18 is configured to recommend an optimal charging station to the customer at an appropriate time by using information recognized from the recognition modules such as the user EVE P.O.I recognition module 10 .

When there is snow or rain forecast from the weather recognition module 17 , the controller 18 may recommend charging just before the snow or rain. In addition, the control unit 18 may recommend the charging station 23 in the room when there is snow or rain forecast from the weather recognition module 17 .

Each module of the electric vehicle 19 charger recommendation system configured as described above may perform the following functions.

The user EVE P.O.I recognition module 10 may search for a charging station 23 that can be charged when a customer arrives based on the preferred charging station 23 and a service membership card held near the preferred charging station 23 .

The user EVE trajectory recognition module 11 may search for a charging station 23 existing within the preferred route 22 (ROUTE) when the customer moves from the customer's origin 27 (POI1) to the destination 28 (POI2). .

The user CPPOI recognition module 12 may recommend a charging station 23 that can be charged based on the customer's charging pattern at the point of departure of the POI.

The charging start/end SoC and charging time/cycle recognition module 132 may recognize the customer's charging panel and recommend an optimal charging station 23 .

The CPI population recognition module 14 may determine the charging status of the charging station 23 based on the time when the customer is charging.

The CPI population recognition module 14 may estimate the density of each charging station 23 as a location-based population.

The EVE departure recognition module may recognize a gentle departure from the POI. The EVE departure recognition module may estimate the departure time based on the moment when the electric vehicle 19 and the user's mobile phone 20 are connected via Bluetooth, or based on the customer's pattern (learning).

The traffic situation recognition module 16 in the EVE trajectory may recommend the charging station 23 in a section where there is no congestion in consideration of the traffic situation at the time when charging is required.

The weather recognition module 17 may recommend the indoor charging station 23 in order to reduce the inconvenience and inconvenience caused by the customer charging while wearing an umbrella when it rains or snows.

The electric vehicle charging station recommendation system of the present invention can provide the following services.

An impact sensor may be installed in the charging port of the electric vehicle 19 . The shock sensor may be configured to detect that the charging socket is inserted into the charging port.

The user EVE P.O.I recognition module 10 detects that the charging station 23 is connected to the charging port of the electric vehicle 19 through the shock sensor, thereby recognizing the customer's charging time and accurately predicting the charging time.

According to this configuration, the user EVE PIO recognition module 10 can accurately predict the charging time even when self-charging at home using the shock sensor.

The user CPI PIO recognition module 12 may receive destination 28 information from the customer's navigation in the electric vehicle 19 control system (or control center).

According to this, the user's CPI PIO recognition module 12 may recommend further charging when the amount of charge in the battery of the customer's electric vehicle 19 is smaller than the amount of charge required to reach the destination 28 .

The CP population recognition module 14 may inform the customer of the usage status information of the charging station 23 when the customer enters within a radius of 300 m from the charging station 23 that can be used with a membership card held by the customer.

At this time, when the customer presses the charging reservation button after checking the usage status information of the charging station 23, the charging reservation can be made immediately.

The electric vehicle charging station recommendation system of the present invention tracks the trace of a customer (member) based on information entering the EV control center 21 when the customer registers rotation information in the EV control center 21 (control system) can do.

According to the present invention, the electric vehicle charging station recommendation system is a POI, a trace that connects the POI (TRAJECTORY), a charging station 23 (CP) visited by a customer within the trace, and a charging station 23 near the charging station 23 where the customer can charge at the time of arrival. Connect all this information, such as chargers, adjusting the charging timing for the weather if the recommended charger is outdoors, and considering the traffic situation and the SoC needed to get to the destination (28) to find the best charger that can be charged and provide customers with the best charger. can recommend

3 is a conceptual diagram illustrating an example of a semantic web as a method of implementing the electric vehicle charging station recommendation system in FIG. 1 .

The present invention proposes a method for implementing an EV charging infrastructure recommendation system for an electric vehicle charging station using a semantic web.

In general, the semantic web refers to a link connecting the web and the web, but in this specification, the semantic web refers to a link connecting the POI and the POI instead of the web.

The electric vehicle charging station recommendation system may view the charging history as one piece of information through the phone 20 or the main system of the charging station 23 and store the information by annotating the link information between the information.

According to the information-to-information link of the semantic web, it is easy to comprehensively determine the information when the charging station 23 is recommended by the controller 18 returning the information recognized by each module to the previous or moving it forward.

The electric vehicle charging station recommendation system includes user information registered in customer management of the control center 21, destination 28 information at the current location through GPS and vehicle navigation, phone 20, main system or GPS of the charging station 23 You can get charging location and charging information through .

For example, referring to FIG. 3 , as user information, ID: User 001, membership card: Ministry of Environment, vehicle model: IONIQ, charging connector (CC, Charging Connector): DC Cha-demo, etc. can be obtained.

When the user's electric vehicle 19 moves from the company (FROM) to the E-Mart Yangjae branch (TO), the charging station (CS, Charge Station), the electric vehicle charging station recommendation system is charged through the phone 20 or the main system of the charging station 23 You can obtain and store information such as charging date and time: 3/8 (Fri) PM 6:20-50, 30% SoC (charge amount) when charging starts, and SoC (charge amount) 60% when charging ends.

In addition, the user's electric vehicle (19) has a different charging date: 3/15 (Fri) 6:15-30 PM from the company to E-Mart Yangjae, SoC (charge amount) 30% when charging starts, SoC (charge amount) when charging ends In the case of charging to 60%, the electric vehicle charging station recommendation system may obtain and store the user's charging information through the phone 20 or the main system of the charging station 23 in the same manner.

In addition, the user's electric vehicle (19) is charged at: 3/8 (Fri) 6:20-50 PM from the E-Mart Yangjae branch, SoC (charge amount) 30% when charging starts, SoC (charge amount) 60 when charging ends %, the electric vehicle charging station recommendation system may obtain and store the user's charging information through the phone 20 or the main system of the charging station 23 in the same way.

After learning the above knowledge, the electric vehicle charging station recommendation system recommends a charging station 23 that can be charged immediately on the way home if the customer's electric vehicle 19 leaves the company after 6 pm on Friday.

4 is a conceptual diagram illustrating a semantic web for implementing the electric vehicle charging station recommendation system according to the present invention.

Referring to FIG. 4 , the electric vehicle charging station recommendation system (EV charging infrastructure) may store charging information of member 1 among members of the Ministry of Environment, which is an EV charging service provider, as follows. The electric vehicle (19) of Member 1, a member of the Ministry of Environment, is a Hyundai electric vehicle and the model is the Ioniq 1. Member 1 moves from POI1 (FROM) to the charging station 23 CP1. At this time, member 1 departs at 5:30 pm on the preferred route 22 (ROUTE 1). Member 1 departs at 6:00 PM after charging (Charging 1) for 30 minutes at CP1 at the charging station 23.

5 is a conceptual diagram for explaining a method of recognizing a user's charging pattern situation by the electric vehicle charging station recommendation system according to the present invention.

The electric vehicle charging station recommendation system can recognize the customer's charging pattern.

The user EVE P.O.I recognition module 10 may recognize a place where the user's electric vehicle 19 frequently goes. For example, the user EVE P.O.I recognition module 10 may recognize a company, house, SP1, and SP2 that the customer frequently visits. Here, SP is an abbreviation of STAY POINT, which means a place where the electric vehicle 19 of the customer (user) stays for more than a preset time. SP1 and SP2 refer to the first and second places where the customer stays for more than a preset time.

The user EVE trajectory recognition module 11 may recognize the preferred route 22 when the customer moves from one place POI1 to another place POI2.

For example, the preferred route 22 may be recognized when the customer moves from home to SP1, from work to SP1, or from home to SP2.

The user CPPOI recognition module 12 may recognize the customer's favorite charging station 23 CP1 or CP2.

The charging start/end SoC recognition module 131 may recognize that the charging amount (startSoC) is less than 40% when the customer starts charging, and the charging amount (endSoC) is less than 70% when the charging ends.

In addition, the charging time/cycle recognition module can recognize that the customer is charging on a weekday evening and periodically charging once every 3 to 4 days.

The CPI population recognition module 14 may recognize the real-time charging state of the user's preferred road 22 and the adjacent total power station.

When a first cluster in which n chargers, for example, CP1, CP3, and CP4 are gathered, and a second cluster in which m chargers CP2, CP5 are gathered are separated from each other, the customer Upon arrival at the cluster or the second cluster, the CPI population recognition module 14 may predict a charger that can be charged without waiting.

The EV start time recognition module 15 may recognize the start time of the electric vehicle 19 when the customer starts the engine by communicating with the electric vehicle 19 through Bluetooth with a mobile device.

For example, the EVE departure time recognition module 15 may recognize that the customer departs from the company at 7 pm on Monday, Tuesday, and Friday and departs from the company at 5:50 pm on Wednesday and Thursday by day of the week. can

6 is a conceptual diagram for explaining a method for inferring a semantic situation for the electric vehicle charging station recommendation system of the present invention to recommend a charging place/time point to a user based on a probability-based state diagram.

First (①), if the customer connects to the electric vehicle 19 via Bluetooth with a mobile device (eg, phone) at 7 pm on Tuesday, the probability of moving to SP1 from the company is 80% (0.8).

In a first step, the user EVE POI recognition module 10 may transmit a POI where the customer frequently goes to the user EVE trajectory recognition module 11 .

The EVE departure time recognition module 15 may transmit the time at which the customer's electric vehicle 19 starts to the user EVE trajectory recognition module 11 to the user EVE trajectory recognition module 11 .

Second (②), the first information that the probability that the customer moves from the company to SP1 is 50% (0.5) or more is transmitted from the user EVE trajectory recognition module 11 to the CP population recognition module 14, , the second information that the probability of charging by the preferred charging cycle is 70% (0.7) or more is transmitted from the user CPPOI recognition module 12 to the CP population recognition module 14, and the preferred charging station (CP) preferred by the customer Upon arrival at POI), the third information that the charging probability is 70% (0.7) or more may be transmitted from the charging start/end SoC recognition module and the charging time/cycle recognition module 132 to the CPI population recognition module 14 .

When the first to third information is transmitted to the CP population recognition module 14, the CP population recognition module 14 recommends a charger with low POPULATION in the vicinity of the customer's preferred road 22 and , the charger is recommended to arrive at the destination 28 in the least amount of time.

7 is a conceptual diagram illustrating a state in which a notification message for charging time and charger recommendation is delivered to a dashboard of a user using a car navigation system. 8 is a conceptual diagram illustrating a state in which a notification message for recommending a charging time and a charging station 23 that can be charged is delivered to a user's phone 20 using a car navigation system.

Referring to FIG. 7 , the electric vehicle charging station recommendation system may deliver a charging time and charger recommendation notification message to a user who uses a car navigation system. The car navigation system may be embedded in the center fascia located between the driver's seat and the passenger seat. A control panel unit 191 that performs navigation, audio (RADIO) functions, and the like, may be disposed above the center fascia.

For example, a notification message saying, "It's time to recharge! You have to wait for at least 20 minutes at "E-Mart (Yangjae Branch)" you go to frequently" may pop up.

The user sees a pop-up notification message and can select "yes" or "no".

Referring to FIG. 8 , a notification message may be delivered to a mobile device (eg, phone 20 ) of a user who uses car navigation.

For example, a notification message "It's time to recharge! Would you like to recommend a charging station 23 that can be recharged immediately?" may pop up on the user's mobile device.

The user may request to recommend a charger by touching the pop-up notification message of the mobile device according to the pop-up notification message.

The configuration of each module provided in the electric vehicle charging station recommendation system will be described in more detail.

9 is a conceptual diagram for specifically explaining the configuration of the user EVE POI recognition module 10 and the user EVE trajectory recognition module 11 of the present invention.

The user EVE POI recognition module 10 may recognize a place (POI) that the user frequently visits by using a Google API.

The user EVE trajectory recognition module 11 may recognize a preferred route 22 (trajectory) while moving to a place frequently visited by the user using a Google API.

The user EVE P.O.I recognition module 10 and the user EVE trajectory recognition module 11 may identify frequently visited places and preferred routes 22 by classifying them by weekday/weekend (by day of the week) and time zone.

For example, the user EVE POI recognition module 10 may recognize a house as a place (POI1 or POI2) where the user mainly stays at night.

The user EVE P.O.I recognition module 10 may recognize the company as a place (POI1 or POI2) where the user mainly stays during the day.

The user EVE P.O.I recognition module 10 may recognize the company as a place (POI1 or POI2) where the user mainly stays during the day.

The user EVE P.O.I recognition module 10 may recognize SP1 (STAY POINT 1) or SP2 (STAY POINT 2) as a place where the user occasionally stays for a predetermined time or longer even if the user does not periodically stay.

The user EVE P.O.I recognition module 10 may recognize SP1 (STAY POINT 1) as a place the user frequently visits on weekdays. SP1 is located between POI1 and POI2. SP1 may be located in the user's preferred path 22 (trajectory) from POI1 to POI2.

The user EVE P.O.I recognition module 10 may recognize SP2 (STAY POINT 2) as a place the user frequently visits on weekends. SP2 is not located between POI1 and POI2 and is not located within a radius of the circumference passing through POI1 and POI2. SP2 may be located on a path moving away from POI2. The SP2 may be located on a path 22 (trajectory) preferred by the user while moving in a direction away from POI2.

10 is a conceptual diagram for explaining the user CP PIO recognition module 12 of the present invention.

The user CPPOI recognition module 12 may recognize the user's favorite charging stations (CP-POI1, CP-POI2, refer to the right map of FIG. 10 ).

The user CPI PIO recognition module 12 may recognize the user's unique number when the user of the electric vehicle 19 authenticates a member at the charging station 23 . The user CPI PIO recognition module 12 may recognize the service provider of the membership card used by the user of the electric vehicle 19 for member authentication at the charging station 23 . Examples of service providers include ChargEV, Aestrepic, Korea Charging (Happy Charger), the Ministry of Environment, and KEPCO.

Examples of service companies linked to Korea Charging and the Ministry of Environment include Jeju Electric Vehicle Service, GNTel, Power Cube, Daeyoung Chaevi, KT, Everon, and POSCO ICT.

The charging station 23 may transmit the logging (LOGGING) of the user's charging information to the control center 21 . Logging means recording various information during operation and making this record to record and preserve the operating state of the system, investigate user habits, and analyze system operation when operating the system.

The charging information may include a charging time, a charging amount of the electric vehicle 19 battery at charging start and charging end. For example, the charging time charged by the user may be 12:30 to 50 minutes in the afternoon. At the start of charging, the charging amount may be 30%. At the end of the charging, the charging amount may be 60%.

11 is a conceptual diagram for explaining the configuration of a charging start/end SoC and a charging time/period recognition module of the present invention.

The charging start/end SoC and charging time/cycle recognition module 13 allows the user to recognize and learn the charging amount (SoC) at the start and end of charging by day and by place.

For example, in FIG. 11 , the X-axis is the charging time, and the Y-axis is the charging amount. At the start of charging, the charging amount may be 30% to 40%. At the end of the charging, the charging amount may be 50% to 60%.

12 is a conceptual diagram for explaining an example of a method for recommending a charging station 23 for an electric vehicle 19 according to the present invention.

The user EVE trajectory recognition module 11 communicates with the user's phone 20 in two-way communication to recognize the start and end times of movement for each trajectory (preferred path 22) of the user. For example, the preferred route 22 among routes frequently used by the user may be a route from the company to SP1. The route 22 preferred by the user to SP1 in the company is mainly available on weekdays.

The user CPI PIO recognition module 12 recognizes the charging station 25 frequently used by the user. The user CPI PIO recognition module 12 may recognize the charging station 26 that can be charged using the user's membership card although it is not frequently used by the user.

The charging stations 25 frequently used by users may be located adjacent to each other in the form of a group. There may be three charging stations 25 gathered in one cluster form. Two of the three charging stations 25 have one charger each. In the other charging station 25, there are three chargers, and the charging station 25 frequently used by users may be located close to the company.

Although not frequently used by the user, the charging station 26 that can be charged using the user's rotating card may be located close to SP1.

The EVE departure time recognition module 15 allows the user to connect the mobile device (phone 20) and the vehicle via Bluetooth at 6 pm, so that the EVE departure time recognition module 15 can recognize that the user is in the vehicle. have.

The electric vehicle charging station recommendation system circles the usage status of the charger 24 in the user's navigation or dashboard when the user of the electric vehicle 19 at each charging station authenticates a member at the charging station 23 or when charging starts in order to recognize the real-time charging situation. ) can be expressed as In the case of the charger 24 filled with a circle, the electric vehicle 19 is being charged at the charging station 23, and in the case of the charger 24 with a hollow circle, the charging station 23 is empty and can be charged without waiting. do.

Users can travel from work to home via SP1. Users can move from home to SP2 on weekends. One charging station 23 may be located in each of the house and SP2. The charging station 23 near the house is a charging station 26 that is not frequently used but can be charged using the user's membership card, and the charging station 23 near the SP2 is a frequently used charging station 25 .

The electric vehicle charging station recommendation system may identify a charging station 23 that can be recharged in the preferred route (TRAJECTORY) to the company-SP1-home based on the user's driving pattern.

Electric vehicle 19 charging recommendation system In proportion to the number of chargers possessed at each charging station, charging stations 23 that can be charged can be found in proportion to the expected charging time after charging starts for each preferred route of the user.

The electric vehicle charging station recommendation system can recommend the charging stations 23 by normalizing the number of chargers in the dense charging stations 23 and calculating the time for the current user to arrive at the place compared to the charging completion time of each charger.

13 is a conceptual diagram for explaining a method of recommending a charging station 23 for an electric vehicle 19 according to an embodiment of the present invention.

First, it can be recognized that the user boards the electric vehicle 19 . The EVE departure time recognition module 15 may detect that the user's phone 20 is connected to the electric vehicle 19 through Bluetooth to recognize that the user has boarded the electric vehicle 19 .

Second, the user sets the destination 28 (POI_ANON2) through the navigation or the phone 20 or the like. The user EVE P.O.I recognition module 10 may determine whether the destination 28 set by the user is a place the user frequently visits.

Third, the charge amount of the user's electric vehicle 19 battery at the user's departure point 27 (POI_home) may be 40%. The control unit 18 of the electric vehicle charging station recommendation system may calculate the amount of charging required to go to the destination 28 .

The control unit 18 may determine whether additional battery charging is required by comparing the current amount of charge with the amount of charge required to reach the destination 28 . If the amount of charge required to go to the destination 28 is greater than the current amount of charge, the controller 18 may calculate an additional charge amount.

Fourth, the user EV CPI PIO recognition module of the electric vehicle charging station recommendation system can recognize that there is a charging station 23 with one charger in the "Tancheon No. 2 public parking lot" on the way of the user.

The charging start/end SoC recognition module 131 may recognize the charging start/end SoC when there is an electric vehicle 19 being charged in "Tancheon No. 2 Public Parking Lot".

The control unit 18 may compare the charging time of the electric vehicle 19 being charged at "Tancheon No. 2 Public Parking Lot" and the arrival time of the user at "Tancheon No. 2 Public Parking Lot". The control unit 18 calculates the charging waiting time of the later user when the user arrives at the "Tancheon No. 2 public parking lot" before the charging of the electric vehicle 19 being charged is completed first.

Fifth, the control unit 18 can recognize that there is a charger that can be charged without waiting at the charging station 23 of the "Asia Park Public Parking Lot" having three chargers on the way of the user.

Seventh, the control unit 18 has to wait more than 15 minutes even if the user arrives at the "Tancheon No. 2 Public Parking Lot" on the way of the user, so the charging station of the "Asia Park Public Parking Lot" with the charging station 23 that can be charged without waiting (23) can be recommended.

The electric vehicle charging station recommendation system can determine that it is beneficial in terms of time even if the user rotates a little.

Eighth, according to the user's selection, the control unit 18 may re-recommend the optimal route to the destination 28, including the charging station 23 and the stopover that can be charged without waiting.

Therefore, according to the present invention, if the customer (user) is registered as a member at the electric vehicle control center, the electric vehicle charging station recommendation system notifies the user at an appropriate time without the customer making a separate search and request for the charger usage status, etc. User convenience can be improved.

In addition, the electric vehicle charging station recommendation system can track the customer's trace based on the information coming into the electric vehicle control center.

In addition, the EV charging station recommendation system includes the location where the EV is parked (POI), the trajectory (preferred road) connecting these locations (POI), the charging station that the customer visits within this trajectory, and the customer near the charging station. The best charging stations that can be charged by connecting all of this information, such as charging stations that can be charged at the time of arrival, adjusting the charging time based on the weather if the recommended charging station is outdoors, and taking into account traffic conditions and the amount of charging required to get to the destination can be found and recommended to customers.

In addition, the charging station operation status referenced by the user is based on the member's authentication/charging information coming from the EV control center, and the density of the charging station can be predicted based on the member's EV density within the GPS radius of the charging station.

In addition, the charger operation status information provided to the user by the electric vehicle charging station recommendation system of the present invention can be obtained more quickly than the charger operation status that the user can check with a delay of 5 to 30 minutes through the Ministry of Environment.

1: Electric vehicle charging station recommendation system
10: User Eevee P.O.I Cognitive Module
11: User Eevee Trejectory Recognition Module
12: User CP PIO cognitive module
13: Charging start/end SoC and charging time/cycle recognition module
131: charging start/end SoC recognition module
132: charging time/cycle recognition module
14 : CP Population Recognition Module
15: Eevee departure point recognition module
16: Traffic situation awareness module in EVE Trejectory
17: weather recognition module 18: control unit
19: electric vehicle 191: control panel unit
20: phone 21: control center
22: preferred route 23: charging station
24: charger 25: frequently used charging station
26: Non-autonomous charging station 27: Departure
28 : destination

Claims (13)

EVE departure time recognition module for recognizing the starting time of the electric vehicle;
a user EV P.O.I recognition module for recognizing a place frequently visited by the user of the electric vehicle;
a user EVE trajectory recognition module for recognizing a preferred route among the routes that the user frequently travels from a departure point to a destination;
a user CPI PIO recognition module for recognizing the user's favorite charging station;
a CPI population recognition module for recognizing the charging state of a charging station adjacent to the preferred road in real time;
a charging start/end charging amount recognition module for recognizing a charging amount at the start and end of charging of the electric vehicle; and
A control unit that is communicatively connected to an electric vehicle or a mobile device owned by a user of the electric vehicle and recommends a charging station capable of charging the electric vehicle to the user in order to charge the amount of charge required for the electric vehicle to reach the destination
including,
The CPI population recognition module clusters charging stations adjacent to the preferred road, and estimates the density by using a ratio of chargers that can be charged from chargers included in the clustered charging stations. According to claim 1,
The control unit is
An electric vehicle charging station recommendation system that recommends another charging station with a shorter charging time even when bypassing the charging station in consideration of the charging standby time when arriving at a charging station adjacent to the preferred route. According to claim 1,
A charging station adjacent to the road from the origin to the destination has a plurality of chargers,
The control unit is
An electric vehicle charging station recommendation system that calculates the time for the user to arrive at the charging station compared to the charging completion time of each of the plurality of chargers, and recommends chargers that can be charged in the order of the charging start time when arriving at the charging station. According to claim 1,
The user EVE P.O.I recognition module is an electric vehicle charging station recommendation system for recognizing frequently visited places by time. According to claim 1,
The user CP P.O.I recognition module is an electric vehicle charging station recommendation system that searches for a charger that can be used with a membership card of the favorite charging station. According to claim 1,
The EV charging station recommendation system further comprising a traffic situation recognition module in EVE trajectory for recognizing the traffic situation on the preferred road when the electric vehicle starts, and recommending a charging station in a non-congested section. According to claim 1,
Further comprising a weather recognition module for recognizing whether it is snowing or raining, wherein the control unit recommends charging just before snow or rain when the recommended charging station is outdoors, or recommends a charging station indoors recommendation system. According to claim 1,
The CPI population recognition module,
An electric vehicle charging station recommendation system for recognizing the charging state of a charging station adjacent to the user's preferred road in real time as the user or customer uploads information at the time of member authentication or charging start to the charging station to the server of the control system. According to claim 1,
The user EV P.O.I recognition module is an electric vehicle charging station recommendation system that searches for a charging station that the user prefers and a charging station that can be charged upon arrival of a registered customer based on a charging service membership card near the preferred charging station. According to claim 1,
The user EVE trajectory recognition module is an electric vehicle charging station recommendation system for searching for a charging station existing on a preferred route when moving from the origin to the destination. According to claim 1,
The user CPI PIO recognition module is an electric vehicle charging station recommendation system for recommending a charging station that can be charged according to the user's charging pattern at the time of departure from the frequently visited place. According to claim 1,
The electric vehicle charging station recommendation system further comprising a charging time/period recognition module for recognizing the user's charging time and charging period. According to claim 1,
The CPI population recognition module identifies the charging status of a charging station based on the time when the user is charging, and based on the location of the charging station, recommends an electric vehicle charging station that estimates the density of each charging station according to the number of chargers possessed by each charging station system.

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